Disclaimer: Use this guide at your own discretion. The author is not responsible for any data loss or security breaches that may occur. Always ensure you understand each step and its implications before proceeding.

This guide walks you through setting up a secure external drive, perfect for backing up sensitive data, securely handing over large data sets, or storing important files. It covers creating an encrypted drive that’s easy to unlock with trusted devices, such as a security key, while remaining highly secure if misplaced. Ideal for safeguarding personal data or business files, it offers practical recovery steps to ensure access even if you change devices.

By following this guide, you will have established a secure and user-friendly encrypted storage solution that leverages:

• LUKS2 Encryption: Provides robust disk encryption.
• TPM2 Integration: Enables automatic unlocking on trusted hardware.
• FIDO2 Tokens: Offers flexible acc

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

日本語で技術的な原稿（書籍の章、記事、解説文）を書く・推敲するときは、以下の規範に従う。